There is a significant number of tasks when we need not just to process an enormous volume of data but to process it as quickly as possible. Delays in tsunami prediction can cost people’s lives. Delays in traffic jam prediction cost extra time. Advertisements based on the recent users’ activity are ten times more popular.
However, stream processing techniques alone are not enough to create a complete real-time system. For example to create a recommendation system we need to have a storage that allows to store and fetch data for a user with minimal latency. These databases should be able to store hundreds of terabytes of data, handle billions of requests per day and have a 100% uptime. NoSQL databases are commonly used to solve this challenging problem.
After you finish this course, you will master stream processing systems and NoSQL databases. You will also learn how to use such popular and powerful systems as Kafka, Cassandra and Redis.
To get the most out of this course, you need to know Hadoop and SQL. You should also have a working knowledge of bash, Python and Spark.
Do you want to learn how to build Big Data applications that can withstand modern challenges? Jump right in!

Instrutores

Sobre Yandex

Yandex is a technology company that builds intelligent products and services powered by machine learning. Our goal is to help consumers and businesses better navigate the online and offline world....

Sobre o Programa de cursos integrados Big Data for Data Engineers

This specialization is made for people working with data (either small or big). If you are a Data Analyst, Data Scientist, Data Engineer or Data Architect (or you want to become one) — don’t miss the opportunity to expand your knowledge and skills in the field of data engineering and data analysis on the large scale.
In four concise courses you will learn the basics of Hadoop, MapReduce, Spark, methods of offline data processing for warehousing, real-time data processing and large-scale machine learning. And Capstone project for you to build and deploy your own Big Data Service (make your portfolio even more competitive).
Over the course of the specialization, you will complete progressively harder programming assignments (mostly in Python). Make sure, you have some experience in it. This course will master your skills in designing solutions for common Big Data tasks:
- creating batch and real-time data processing pipelines,
- doing machine learning at scale,
- deploying machine learning models into a production environment — and much more!
Join some of best hands-on big data professionals, who know, their job inside-out, to learn the basics, as well as some tricks of the trade, from them.
Special thanks to Prof. Mikhail Roytberg (APT dept., MIPT), Oleg Sukhoroslov (PhD, Senior Researcher, IITP RAS), Oleg Ivchenko (APT dept., MIPT), Pavel Akhtyamov (APT dept., MIPT), Vladimir Kuznetsov, Asya Roitberg, Eugene Baulin, Marina Sudarikova....